"... In most studies of contingency assessment participants judge the magnitude of the relationship between cues and outcomes. This judgment is a conflated measure of the participant’s sensitivity to the cue-outcome relationship, and his or her response bias. A psychophysical model (signal detection theo ..."

In most studies of contingency assessment participants judge the magnitude of the relationship between cues and outcomes. This judgment is a conflated measure of the participant’s sensitivity to the cue-outcome relationship, and his or her response bias. A psychophysical model (signal detection theory, SDT) can be used to dissect the independent contributions of sensitivity and bias to contingency judgment. Results of an experiment concerning cue-interaction (blocking) illustrate the utility of applying SDT to understanding contingency assessment. Most accounts of such assessment are associative (derived primarily from Pavlovian conditioning experiments with non-human animals). A psychophysical analysis of contingency assessment is not an alternative to such associative accounts. The SDT analysis supplements (not replaces) learning principles with psychophysical principles.

"... that cue interaction effects in human contingency judgments reflect processing that occurs after the acquisition of information. This finding is in conflict with a broad class of theories. We present a new postacquisition model, the criterion-calibration model, that describes cue interaction effects ..."

that cue interaction effects in human contingency judgments reflect processing that occurs after the acquisition of information. This finding is in conflict with a broad class of theories. We present a new postacquisition model, the criterion-calibration model, that describes cue interaction effects as involving shifts in a report criterion. The model accounts for the Siegel et al. data and outperforms the only other postacquisition model of cue interaction, Stout and Miller’s (2007) SOCR model. We present new data from an experiment designed to evaluate a prediction of the two models regarding reciprocal cue interaction effects. The new data provide further support for the criterion-calibration model.